Identification of candidate genes and residues for improving nitrogen use efficiency in the N-sensitive medicinal plant Panax notoginseng

Background Nitrogen (N) metabolism-related key genes and conserved amino acid sites in key enzymes play a crucial role in improving N use efficiency (NUE) under N stress. However, it is not clearly known about the molecular mechanism of N deficiency-induced improvement of NUE in the N-sensitive rhizomatous medicinal plant Panax notoginseng (Burk.) F. H. Chen. To explore the potential regulatory mechanism, the transcriptome and proteome were analyzed and the three-dimensional (3D) information and molecular docking models of key genes were compared in the roots of P. notoginseng grown under N regimes. Results Total N uptake and the proportion of N distribution to roots were significantly reduced, but the NUE, N use efficiency in biomass production (NUEb), the recovery of N fertilizer (RNF) and the proportion of N distribution to shoot were increased in the N0-treated (without N addition) plants. The expression of N uptake- and transport-related genes NPF1.2, NRT2.4, NPF8.1, NPF4.6, AVP, proteins AMT and NRT2 were obviously up-regulated in the N0-grown plants. Meanwhile, the expression of CIPK23, PLC2, NLP6, TCP20, and BT1 related to the nitrate signal-sensing and transduction were up-regulated under the N0 condition. Glutamine synthetase (GS) activity was decreased in the N-deficient plants, while the activity of glutamate dehydrogenase (GDH) increased. The expression of genes GS1-1 and GDH1, and proteins GDH1 and GDH2 were up-regulated in the N0-grown plants, there was a significantly positive correlation between the expression of protein GDH1 and of gene GDH1. Glu192, Glu199 and Glu400 in PnGS1 and PnGDH1were the key amino acid residues that affect the NUE and lead to the differences in GDH enzyme activity. The 3D structure, docking model, and residues of Solanum tuberosum and P. notoginseng was similar. Conclusions N deficiency might promote the expression of key genes for N uptake (genes NPF8.1, NPF4.6, AMT, AVP and NRT2), transport (NPF1.2 and NRT2.4), assimilation (proteins GS1 and GDH1), signaling and transduction (genes CIPK23, PLC2, NLP6, TCP20, and BT1) to enhance NUE in the rhizomatous species. N deficiency might induce Glu192, Glu199 and Glu400 to improve the biological activity of GS1 and GDH, this has been hypothesized to be the main reason for the enhanced ability of N assimilation in N-deficient rhizomatous species. The key genes and residues involved in improving NUE provide excellent candidates for the breeding of medicinal plants. Supplementary Information The online version contains supplementary material available at 10.1186/s12870-024-04768-4.


Background
Nitrogen (N) is a limiting factor for crop yield.To meet the increasing demand for food from the growing global population, over 110 Tg of N fertilizer is applied annually to improve crop yields [1].However, less than 40% of applied N fertilizer is absorbed by crops, the remaining N fertilizer is lost to the environment through processes such as volatilization, leaching, surface runoff, or microbial consumption [2,3].Hence, N use efficiency (NUE) in plants has to be improved [4].NUE is a complex trait influenced by both genetic and environmental factors [5].NUE mainly depends on how plants uptake inorganic N from the soil, assimilate nitrate (NO 3 -) and ammonium (NH 4 + ) [6].A better understanding of N uptake, transportation and assimilation within the plant is crucial for breeding for crops with high NUE and for the development of sustainable agriculture.
The low-affinity transport system (LATS) and the highaffinity transport system (HATS) ensure an efficient uptake over a wide range of external NO 3 -concentrations [7].Phosphorylation of a threonine residue, Thr101, lead to a switch of NRT1.1 from low-to high-affinity state [8].The expression of NRT2/NPF initiates HATS in the N-deficient condition [9].Overexpression of OsNRT2.1 and OsNRT2.3 in Oryza sativa has been found to improve NUE and yields under the N deficiency condition [10,11].NO 3 -are degraded to NH 4

+
, then NH 4 + form amino acid through catalysis by N metabolism-related enzyme, as reflected by nitrite reductase (NiR), glutamine synthetase (GS) and glutamate dehydrogenase (GDH) [9].Overexpression of DvGS1/2 and OsGS1 is positively associated with the biomass and NUE in the N-deficient Dunaliella viridis, Arabidopsis thaliana and O. sativa [12][13][14].Meanwhile, the enhanced NO 3 -signal-sensing and transduction pathways might promote N uptake and utilization, and thus improve NUE [15].The increased expression of NRT1.1, NRT2.1, NIA, NIR1, and GS2 in NLP7-overexpressing A. thaliana cloud improve the biomass and NUE under N stress [16].Extensive reports are available on N-mediated regulation of enzymes and genes involved in N metabolism [17][18][19].Significantly, Pro492 and Ser487 residue of NRT1.1 is important for NO 3 transport activity and NUE in A. thaliana [20].Gln433 and Tyr512 residue play an important role in a comprehensive understanding of NPF genes for low N tolerance in Setaria italica [21].Thus, dissecting the three-dimensional (3D) information and molecular docking models of key genes for N uptake, transportation and assimilation is important for improving plant NUE.
Panax notoginseng is a perennial rhizomatous medicinal plant and is also an N-sensitive species in the Araliaceae family.The application of N fertilizer in P. notoginseng cultivation can be as high as 337.5-450 kg•ha - 1 •year -1 , which is two times the amount of crops like Zea mays and O. sativa, and four to five times the amount of Nicotiana tabacum.Excessive N fertilizer not only reduces NUE and increases production costs, but also causes continuous cropping barrier, severe field diseases, and quality decline in P. notoginseng [22].NUE is significantly increased in two-and three-year-old P. notoginseng grown under the N deficient condition, and high N application significantly inhibits N uptake and NUE, and reduces biomass accumulation [23,24].It is worth noting that GS, GDH, and NR activity in the N-deficient P. notoginseng are higher than those in N-surplus groups (450 kg•ha -1 ), and the expression levels of GS1, GDH1, NIR, NIA, and NPF are up-regulated under the N deficiency levels [22].However, it is still unknown about the molecular mechanisms underlying the low N tolerance in P. notoginseng.Although N uptake and NUE has been preliminarily studied in P. notoginseng under N regimes [22,24], the underlying reason for the N regulation of NUE remain largely undetermined.
In this study, N uptake and utilization indicators and N metabolism-related enzymes and genes were analyzed in two-year-old P. notoginseng grown under N 0 (without N addition), N 7.5 (112.5 kg•ha -1 , mild N deficiency), and N 15 (225 kg•ha -1 , normal N) condition.Key genes for N assimilation in response to N deficiency, coupled with the multi-omics analysis, 3D information and molecular docking models, were further identified.A systematic investigation was conducted on the expression of the genes and residues related to N uptake, transport, assimilation, NO 3 -signal-sensing and transduction in the N-deficient plants.The present study would provide a valuable information for selecting candidate genes to improve NUE and further for investigating the function of N assimilation-related enzymes in the medicinal plants, such as P. notoginseng.

Results
The effect of N levels on Carbon(C) and N contents in P. notoginseng N content of leaf and stem was significantly increased in the N 15 -treated plants (Table 1).There was no significant difference in N content between the N 7.5 and N 15 treatments, except for the stem (Table 1).C content in all tissues showed no significant difference among treatments (Table 1).

Responses of N uptake and utilization to N regimes
Total N uptake (TN), total N uptake per unit root length (TNL), and root N content per unit root length (RNL) were significantly decreased in the N 0 -grown plants compared with the N 7.5 -and N 15 -grown plants (Fig. 1A).A proportion of N distribution to shoot was decreased with increasing N supply, while the proportion of N distribution to root was increased (Fig. 1B).There was no significant difference in the harvest index among N regimes (Fig. 1C).The maximum values of N use efficiency in biomass production (NUEb), N uptake efficiency and NUE were recorded in the N 0 -grown plants (Fig. 1C).N partial factor productivity (NPFP) and N agronomic efficiency (NAE) were no significantly different between the N 7.5 and N 15 treatments (Table 2).N contribution rate (NCR) was significantly increased in the N 15 -treated plant, which the recovery of N fertilizer (RNF) was decreased (Table 2).

DIA-proteome quality control and differential protein analysis
A total of 53078 peptides and 8042 proteins were identified in the proteome (Figure S2A).The statistical analysis of the number of peptides per protein showed that most proteins had 1-5 or >10 peptide segments (Figure S2B).7085, 3053, and 5902 proteins were annotated in the GO, KEGG KOG database among the 8042 proteins, respectively (Figure S3A).There were 65 up-regulated and 247 down-regulated proteins in the N 0 vs N 7.5 group, and 84 up-regulated and 269 down-regulated proteins in the N 0 vs N 15 group (|log 2 (1.5)| ≈ 0.58, Figure S3B).For GO enrichment analysis, The differentially expressed proteins were mainly annotated to processes such as "metabolic process", "cellular process", "cell part" and "response to stimulus" (Figure S4).KEGG pathway analysis revealed that the differentially expressed proteins in the N 0 vs N 7.5 and N 0 vs N 15 comparison groups were mainly enriched in metabolic pathways such as "biosynthesis of secondary metabolites "and "carotenoid biosynthesis", "N metabolism" (Figure S5).As shown in Figure S6, trend 1, trend 0, and trend 6 were the three largest clusters, with 270, 81, and 65 differentially expressed proteins, respectively.Trend 0 were significantly up-regulated under the N 0 condition compared with the N 7.5 and N 15 conditions (Figure S6).The functions of Trend 0 mainly included pathways such as "metabolic pathways", "starch and sucrose metabolism", and "N metabolism" (Figure S7).

Responses of N metabolism-related enzymes activity to N regimes
There was no significant difference in the activity of nitrite reductase (NiR) among N regimes (Fig. 1D).The maximum and minimum values of glutamine synthetase (GS) and glutamate synthetase (GOGAT) activity were recorded in the N 15 -grown plants, respectively (Fig. 1D).
The activity of glutamate dehydrogenase (GDH) significantly decreased with increasing N supply (Fig. 1D).

N deficiency reduces the occupation of N in root
An enhancement of N uptake efficiency and N use efficiency is a primary strategy to improve N efficiency [25].The ability of plants to absorb N would be obviously weakened under the low N condition [26].N uptake considerably affects N use efficiency [27].Herein, N deficiency enhances NUE, NUEb and RNF (Fig. 1A, C; Table 2), and the proportion of N distribution to root was decreased.These results further confirm that the higher NUE under the low N might be closely linked to the occupation of N by root [28].
The RNL is commonly used to reflect the occupation of N by roots [29].Our results demonstrated that N deficiency significantly reduces the occupation of N in roots (Fig. 1).It is worth noting that the proportion of N distribution to shoot was increased (Fig. 1B).
We speculate that the limited N absorbed by the roots might be more extensively transported to the aboveground parts to maintain the survival under the N-deficient condition [26].Overall, N deficiency reduces the occupation of N in root and thus changes NUE.

The roles of Glu192, Glu199 and Glu400 in the N assimilation
N assimilation is a core process for N utilization in plants [39].NUE can be enhanced by the expression of N assimilation-related gene OsNiR in the N-deficient O. sativa [40].NiR enzyme activity was not significantly different among N regimes (Fig. 1D), but the expression of gene NIR1 and protein NIR1 up-regulated with increasing N supply (Figs. 3, 4 and 7B).Our results revealed that N supply might promote an increase in NiR quantity, but the structure and composition of NiR did not cause a change in the activity of nitrite (NO 2 -) being reduced to NH 4 + under N regimes [27,41].Additionally, GS1-1 is the dominant gene induced by low N to synthesis NH 4 + and glutamine into glutamate [42].OsGS1;2 and DvGS1/2 over-expression has been shown to enhance the total protein content, NUE and biomass accumulation in the N-deficient plants [12][13][14].We speculate that the expression of GS1-1 contributes to the synthesis of glutamate in the N-deficient plants as demonstrated by a number of investigation (Fig. 3) [43].The expression of gene ASN3 and protein ASN3 were up-regulated in the N-deficient P. notoginseng and Lactuca sativa, indicating that more NH 4 + is synthesized into amino acids (Figs. 3 and 4) [44].A number of studies has demonstrated that the activity of GDH enzyme is increased under the low N condition [45][46][47].In the present study, N deficiency up-regulates the expression and activity GDH, and there was a significantly positive correlation between protein GDH1 and gene GDH1 (Fig. 7B).N mediate post-translational phosphorylation modifications of GDH2, resulting in an inconsistent change at the gene and protein levels (Figs. 3 and 4) [48].These results indicate that GDH1 might play an important role in response to N deficiency.As such, gene GS1-1 and protein GDH1 are suggested as the prospective key genes regulating the N deficiencydriven enhancement of N assimilation, and they contribute to the improvement of NUE under the low N condition.
The method of molecular docking is popular to study the biological activity of N affecting plant NUE [21].PnGS1-NH 4 + interaction analysis revealed that Glu192 and Glu199 were strictly conserved and located around the middle of the catalytic pocket (Fig. 10).Similar results have been reported in A. thaliana, Z. mays and Medicago truncatula GS proteins [49].The strictly conserved amino acids Glu192 and Glu199 of GS in M. truncatula are positioned approximately in the middle of cavity, Fig. 7 Co-expression analysis of key genes and proteins in the N uptake and transport pathway (A).Co-expression analysis of key genes and proteins in the N assimilation pathway (B).Co-expression analysis of key genes and proteins in the nitrate signal-sensing and transduction pathway (C).Yellow nodes represent proteins (larger sizes are associated with more genes), and green nodes indicates genes.Red edges represent positive correlations (PPC > 0.8) and blue edges represent negative correlations (correlations are stronger with thicker lines) Fig. 8 Amino acid sequence alignment and three-dimensional (3D) protein structure prediction of GS1 in Arabidopsis thaliana (AtGS1), P. notoginseng (PnGS1), Solanum tuberosum (StGS1) and Zea mays (ZmGS1).The AtGS1, PnGS1, StGS1 and AtGS1 nucleotide sequence was translated into protein sequence (A).Highly accurate protein structure prediction with AlphaFold2, save its PDB file and visualize it using PyMOL software, and the predicted 3D protein colored light purple is shown in cartoon representation (B) favorably located to mediate cation coordination [50,51].The gene expression of GS1 were up-regulated in the N 0 -grown plants (Fig. 3).We speculate that N deficiency induces the conserved residues Glu199 and Glu192 to bind more NH 4 + , consequently catalysing the synthesis of more glutamine from glutamate.Additionally, Fig. 9 Amino acid sequence alignment and 3D protein structure prediction of GDH1 in in A. thaliana (AtGDH1), P. notoginseng (PnGDH1), S. tuberosum (StGDH1) and Z. mays (ZmGDH1).The AtGDH1, PnGDH1, StGDH1 and AtGDH1 nucleotide sequence was translated into protein sequence (A).Highly accurate protein structure prediction with AlphaFold2, save its PDB file and visualize it using PyMOL software, and the predicted 3D protein colored light purple is shown in cartoon representation (B) site-directed mutagenesis and 3D structure determination of glucoamylase has identified Glu400 as the general base catalyst, which is conducive to the synthesis of more amino acids [52,53].PnGDH1-NH 4 + interaction analysis revealed that Glu400 directly binds to NH 4 + (Fig. 11), and the expression and activity of GDH1 were up-regulated in the N 0 -treated plants (Figs. 1, 3 and 4).These results suggest that the high expression of GDH1 enhances the docking ability of Glu400 to NH 4 + and promotes the synthesis of glutamate in the N-deficient plants.Similarly, the residues of conserved proline and T101 significantly enhance NO 3 -transport activity and NUE in the N-deficient A. thaliana [20].Therefore, N deficiency induces Glu residues (as referred to Glu192, Glu199 and Glu400) to enhance the biological activity of GS1 and GDH1, thereby improving N assimilation.A review of previous studies on usea-urease docking complexes has suggested that different species (as reflected by Glycine max and M. truncatula) could share common interacting residues as well as may have some other uncommon residues at species-dependent way [54].In the present study, Glu192 and Glu199 in P. notoginseng and S. tuberosum were identified as hotspot residues residing in GS1 (Figs. 10, S12).We speculate that the preference for NO 3 -is the main reason for the similar GS1 activity in the rhizomatous species P. notoginseng and S. tuberosum.Overall, the residues of Glu192, Glu199 and Glu400 are suggested as the prospective key hotspot residues regulating the N deficiency-driven enhancement of N assimilation in the rhizomatous species.

Conclusion
We have proposed a hypothetical genetic regulatory network (Fig. 12), and have suggested that N deficiency promotes the expression of key genes involved in N uptake, transport, assimilation, signaling and transduction, and thus enhance NUE in the rhizomatous medicinal plant P. notoginseng.NPF8.1, NPF4.6, AMT, AVP and NRT2 family genes might be considered as the key genes regulating the N deficiency-promoted N uptake.The genes of NPF1.2 and NRT2.4 might mediate N deficiency-induced N transport from roots to shoots.N deficiency would induce the residues of Glu192, Glu199 and Glu400 to enhance the biological activity and expression of GS1 and GDH1, thereby improving N assimilation.The expression of genes CIPK23, PLC2, NLP6, TCP20, and BT1, contributes to NO 3 -signal-sensing and transduction under the N-deficient condition.In summary, the genes and residues proposed as being involved in N metabolism would provide excellent candidates for further genetic improvement in the NUE of rhizomatous medicinal plants.

Experiment design
A potted experiment was conducted from January to November 2021 in Kunming, Yunnan Province, southwestern China (longitude 102°45' , latitude 25°08').Seedlings were harvested from the plants of 1-year-old P. notoginseng (Burk.)F. H. Chen.that were cultivated at the experimental farm of Wenshan Miao Xiang P. notoginseng Industrial Co., Ltd., China.Healthy rhizome of P. notoginseng were selected in our experiments and transplanted to a plastic pot (35×40 cm) on January 2021.The pot experiment was conducted in a controlled environment growth chamber with a light intensity of about 10% [58].The physicochemical properties of the soil are shown as following: pH 6.02, organic matter 11.04 g•kg -1 , hydrolysable N 54.58 mg•kg -1 , available phosphorus (P) 0.46 mg•kg -1 , available potassium (K) 36.67 mg•kg -1 , total N 0.10%, total phosphorus 0.10%, total potassium 0.79 g•kg -1 .
In the present study, a completely randomized design was used with three replicates for each treatment, including three N addition levels (Figure S1): (i) without N addition (without N addition), N 0 ; (ii) 112.5 kg•N•ha -1 (mild N deficiency), N 7.5 ; (iii) 225 kg•N•ha -1 (normal N), N 15 .Each replicate consisted of 40 pots.In addition to N fertilizer, the application levels of phosphorus fertilizer (225 kg•P 2 O 5 •ha -1 ) and potassium fertilizer (450 kg•K 2 O•ha -1 ) were the same for all treatments.The fertilizers applied in the study were compound fertilizer (N:P:K = 32:4:0), calcium superphosphate (N:P:K = 0:52:34), and potassium sulfate (N:P:K = 0:0:52).Fertilization was applied four times in mid-May, June, July, and mid-August 2021.Conventional pesticides were used to control weeds, diseases, and pests.In November 2021, roots were collected under different N treatments, washed, and then flash-frozen in liquid N and stored at -80°C for transcriptome and metabolome analyse.

Determination of C and N content
Plant was separated into taproot, rhizome, fibrous roots, stem and leaf.The taproot, rhizome, fibrous roots, stem and leaf were dried at 60℃ to constant weight for 96 h.Dry matter was determined.The dried samples were ground and passed through a 100-mesh sieve for further analysis.The C and N content were determined using an elemental analyzer (Vario EL III; Elementar analysisysteme GmbH Hanau, Germany).

Calculation of N use efficiency
Based on biomass and N content, N uptake and utilization related parameters were calculated as described by Gupta et al. [59]: Total N uptake (TN, mg•plant -1 ) = above-ground N content + below-ground N content; Total N uptake per unit root length (TNL, mg•cm -1 ) = total N uptake per plant / total root length per plant; Root N content per unit root length (RNL, mg•cm -1 ) = Root N content / total root length per plant; Proportion of N distribution to shoot (%) = above-ground N content / total N uptake; Proportion of N distribution to root (%) = root N content / total N uptake; N use efficiency (NUE, kg•kg -1 ) = yield (below-ground dry weight) / total N uptake; N agronomic efficiency (NAE, kg•kg -1 ) = (yield with N application -yield without N application) / N application rate; Recovery of N fertilizer (RNF, %) = (above-ground N content with N application -aboveground N content without N application)/N application rate × 100; N contribution rate (NCR, %) = (yield with N application -yield without N application) / yield with N application × 100; N partial factor productivity (NPFP, kg•kg -1 ) = yield with N application / N application rate; N use efficiency in biomass production (NUEb, g•DW•g - 1 •N) = below-ground dry matter accumulation per plant / below-ground N accumulation per plant; Harvest index = root dry weight at harvest / plant dry weight at harvest; N harvest index = N uptake in roots at harvest / total N accumulation per plant; N uptake efficiency (kg•kg -1 ) = total N uptake per plant / N application rate.

Determination of enzyme activity
The activity of N metabolism-related enzymes was assayed according to Li [60].The measurement of the activity of NiR (G0408F), NADH-GOGAT (G0403F), GS (G0401F), and NADH-GDH (G0405F) were carried out by kits from Suzhou Gores Biotechnology Co., Ltd.

RNA-Seq and annotation
The experimental process of transcriptome sequencing includes RNA extraction, RNA quality detection, library construction, and sequencing.Firstly, total RNA was extracted from the roots of P. notoginseng.The integrity of the sample RNA and the presence of DNA contamination were examined using an RNase-free agarose gel electrophoresis.Then, enriched mRNA fragments were fragmented into short fragments using a fragmentation buffer, and reverse transcribed into cDNA using Illumina's NEBNext Ultra RNA Library Prep Kit (NEB#7530, New England Biolabs, Ipswich, MA, USA).The purified double-stranded cDNA was end-repaired, A-tailed, and ligated with sequencing adapters.200 bp cDNA was selected using AMPure XP beads, PCR amplified, and purified with AMPure XP beads again to obtain the library.Guangzhou Genedenovo Biotechnology Co., Ltd.sequenced the obtained cDNA library on the Illumina Novaseq6000 platform.Finally, 9 cDNA libraries representing three replicates and three N levels were .The black balls showed carbon atoms, the blue balls showed nitrogen atoms whereas the red balls showed the oxygen atoms.The residues involved in non-bonding interactions were shown as red bristles constructed, and the transcriptome was sequenced on the Illumina Hiseq platform using P. notoginseng genome (PRJNA608068; http:// herba lplant.ynau.edu.cn/) as the reference genome [61].After obtaining the gene expression levels for each sample, differentially expressed genes (DEGs) among samples were analyzed.The input data for gene differential expression analysis were the reads count data obtained in the gene expression level analysis, and DESeq2 software was used for analysis.Based on the differential analysis results, genes with FDR (false discovery rate) < 0.05 and |log 2 FC| > 1were defined as significantly differentially expressed genes [62,63].After selecting differentially expressed genes according to the analysis purpose, a clustering heat map of different samples was generated for functional annotation, enrichment analysis, trend analysis, and other analyses of DEGs.

Determination and analysis of data-independent acquisition (DIA) proteomics
In November 2021, samples grown under different N treatments were collected and immediately washed, frozen in liquid N, and stored at -80℃ for DIA protein profiling analysis.DIA protein profiling analysis included processes such as protein extraction, denaturation, reduction, alkylation, enzymatic digestion, and desalting of peptides.The tissue samples were pre-processed Fig. 12 A regulatory mechanism of N deficiency-driven enhancement of NUE has been proposed in the rhizomatous species P. notoginseng using the iST sample pre-processing kit (PreOmics, Germany).After grinding the samples in liquid N, an appropriate amount of sample was taken and added to 50 µL of lysis buffer.The mixture was then heated at 95℃ with 1000 rpm for 10 min.After cooling to room temperature, the sample was incubated with trypsin digestion buffer at 37℃ and 500 rpm for 2 h.The reaction was then stopped by adding the stop buffer.Peptide desalting was carried out using the iST cartridge provided in the kit, with 2 × 100 µL wash buffer for elution.The eluted peptides were vacuum-dried and stored at -80℃.For analysis, each sample was mixed with 30 µL of solvent A (A: 0.1% formic acid aqueous solution) to form a suspension, and 9 µL of the mixture was taken and mixed with 1 µL of 10 × iRT peptides.The mixture was then separated using nano-LC and analyzed using online electrospray ionization tandem mass spectrometry.Before mass spectrometry detection, Biognosys iRT Kit was added to each sample as a quality control reagent, and the retention time (RT) of peptides in chromatography was calibrated using the QuiC (Biognosys) [64] software for quality control of the raw mass spectrometry data.The Pulsar [65] software was then used to build a database and analyze the DIA data results based on the DDA reference database to identify proteins.Qualitative results and quantitative results in all samples were output when a protein was detected.
The detected protein group was annotated using the GO, KEGG, and KOG databases [66], and the annotation results were statistically analyzed.Based on the expression results of each sample, PCA analysis was used to analyze and calculate the Pearson correlation coefficient between samples to understand the repeatability of the samples and help exclude outliers.Subsequently, proteins with significant differences between groups were selected based on the absolute value of FC greater than 1.5 (|log 2 (1.5)| ≈ 0.58, P < 0.05), and the differentially expressed proteins were subjected to GO, KEGG, GSEA, interaction network, and trend analysis.

Combined transcriptome and proteome analysis
Differently expressed genes and differentially expressed proteins are analyzed in combination The KEGG pathway was mapped to genes and proteins with changed transcriptomics and proteomics, and histograms were produced to show pathway enrichment with differential proteins and genes.Correlation analysis was performed for DEGs and proteins in each group.Pearson's correlation coefficients (PCCs) were determined using the Cor tool in R (www.r-proje ct.org).Genes and proteins with a |PPC| > 0.80 were created a network diagram to show correlation.

qRT-PCR verification
qRT-PCR was performed according to the method described by Xiong et al. [70].YLS8 was used as the reference gene [22].Primers of qRT-PCR are listed in Table S1.Three replicates were performed for each gene and sample.Results were calculated using the formula 2 -ΔΔCt .

Statistical analysis
GraphPad Prism 8 (GraphPad Software Inc. USA) and IBM SPSS Statistics 20.0 (IBM Corp. USA) was used for statistical analyses.One-way analysis of variance (ANOVA) test was performed to compare the differences between N regimes.The integrative analysis was performed using the R software, and the co-expression networks were visualized using the Cytoscape (version 3.7.1).

Fig. 2 Fig. 3
Fig. 2 Response of N uptake-and transport-related genes to N levels.Average genes intensity is color key scale according the scale in the middle upper part

Fig. 4
Fig. 4 Response of N uptake-, transport-and assimilation-related proteins to N levels.The pathway map was prepared by using KEGG PATHWAY Database.With each box, each column is different nitrogen treatment (from left to right: N 0 , N 7.5 and N 15 ) as shown in the middle upper part.Average proteins intensity is color key scale according the scale in the middle upper part

Fig. 5
Fig.5 Response of nitrate signal-sensing and transduction pathway-related genes to N levels.Average genes intensity is color key scale according the scale in the middle upper part

Fig. 6
Fig. 6 Response of nitrate signal-sensing and transduction pathway-related proteins to N levels.The pathway map was prepared by using KEGG PATHWAY Database.With each box, each column is different nitrogen treatment (from left to right: N 0 , N 7.5 and N 15 ) as shown in the middle upper part.Average proteins intensity is color key scale according the scale in the middle upper part

Tabel 1
Effects of nitrogen levels on N and organic carbon (C) content in Panax notoginseng

Table 2
Effects of N levels on N agronomic efficiency in P. notoginseng NPFP N partial productivity, NAE N agronomic efficiency, NCR N contribution rate, RNF Recovery of N fertilizer Values followed by different letters are significantly different at P < 0.05